Seizure forecasting: Where do we stand?

Abstract

A lot of mileage has been made recently on the long and winding road toward seizure forecasting. Here we briefly review some selected milestones passed along the way, which were discussed at the International Conference for Technology and Analysis of Seizures—ICTALS 2022—convened at the University of Bern, Switzerland. Major impetus was gained recently from wearable and implantable devices that record not only electroencephalography, but also data on motor behavior, acoustic signals, and various signals of the autonomic nervous system. This multimodal monitoring can be performed for ultralong timescales covering months or years. Accordingly, features and metrics extracted from these data now assess seizure dynamics with a greater degree of completeness. Most prominently, this has allowed the confirmation of the long‐suspected cyclical nature of interictal epileptiform activity, seizure risk, and seizures. The timescales cover daily, multi‐day, and yearly cycles. Progress has also been fueled by approaches originating from the interdisciplinary field of network science. Considering epilepsy as a large‐scale network disorder yielded novel perspectives on the pre‐ictal dynamics of the evolving epileptic brain. In addition to discrete predictions that a seizure will take place in a specified prediction horizon, the community broadened the scope to probabilistic forecasts of a seizure risk evolving continuously in time. This shift of gears triggered the incorporation of additional metrics to quantify the performance of forecasting algorithms, which should be compared to the chance performance of constrained stochastic null models. An imminent task of utmost importance is to find optimal ways to communicate the output of seizure‐forecasting algorithms to patients, caretakers, and clinicians, so that they can have socioeconomic impact and improve patients' well‐being.

Early and widespread engagement of the cerebellum during hippocampal epileptiform activity Format: Brief Communication

“…Indeed, our work highlights that the cerebellum should be considered as an area of interest even in cases where the seizure focus is believed to be well-defined. The cerebellum, and its early modulation, may also provide a means for seizure prediction or forecasting 23,24 with a very short temporal window, which would allow effective, time-restricted, interventions. Given that on-demand modulation of the cerebellum has been shown to inhibit seizures (for both absence and temporal lobe epilepsy 4,9,10,12 ), this raises the possibility of both early seizure detection/prediction and closed-loop intervention occurring from cerebellar locations.…”

Passive and active markers of cortical excitability in epilepsy

“…Furthermore, it cannot be ruled out that a single biomarker will prove insufficient and multiple biomarkers will be required to secure a reliable detection or prediction. 1 How do we translate new epilepsy biomarkers into clinical practice? First, we must validate proposed biomarkers in large external datasets, which will require improved methods of data-sharing, or federated approaches to sharing code across centers.…”

“…Biomarkers should be easily, accurately, and reproducibly detectable but may be specific for a certain time window, condition, or syndrome. Furthermore, it cannot be ruled out that a single biomarker will prove insufficient and multiple biomarkers will be required to secure a reliable detection or prediction 1 …”

“…We limit our scope to biomarkers to identify epileptic cortex rather than biomarkers for seizure prediction, which are discussed in a separate article in this issue. 1…”

“…After presenting an overview of these techniques, we turn our focus to several key questions that must be addressed to allow these techniques to be utilized by clinicians. We limit our scope to biomarkers to identify epileptic cortex rather than biomarkers for seizure prediction, which are discussed in a separate article in this issue 1 …”